Sampling in Research: Principles, Methods, and Applications

Abstract

Sampling techniques in research are crucial processes for selecting a sample group from a population to obtain accurate and reliable data without needing to collect information from the entire population. Sampling reduces limitations related to time, budget, and personnel, enabling researchers to draw conclusions and make generalizations about the entire population accurately and systematically. The main sampling techniques include simple random sampling, stratified sampling, cluster sampling, and systematic sampling. These techniques enhance precision and reduce bias in data collection. Additionally, non-probability sampling techniques such as purposive sampling, quota sampling, convenience sampling, and snowball sampling are suitable for qualitative research or cases requiring access to specific target groups. Proper and appropriate sampling processes allow researchers to collect data effectively and reliably, making research findings reflective of reality and practically applicable. Researchers should carefully consider and select sampling techniques that align with their research objectives and population characteristics to obtain high-quality results that can be effectively applied in real-world situations